The Taylor rule presents a traditional approach to guiding and evaluating contemporary monetary policy as a function of inflation and economic slack. While the responsibilities of the Federal Reserve (Fed) include price stability and long-run growth, its mission has grown to include financial stability. Surprisingly, the question of whether financial stability ought to be considered as an element of monetary policy is hotly contested. This study aims to determine whether policymakers’ discussions of financial stability and other factors systematically explain deviations of observed policy rates from the rates implied by the Taylor rule. To this end, we conduct content analysis of the Fed’s monetary policy discussions to discover actual topics that enter into policy. We offer two main findings: First, discussion themes extracted from released Federal Open Market Committee meeting minutes provide explanatory power beyond standard Taylor rule variables. Second, additional explanatory power is provided by a tri-mandate policy rule that accounts for changes in the economic and financial system as moderated by the evolving preferences of the policymakers. We show that a discussion-based thematic model with financial stability dominates Taylor-type rules during normal times. Moreover, the tri-mandate policy model with financial stability dominates Taylor-type rules in zero lower bound conditions. Taken together, these findings reveal that financial stability has mattered to the Fed continuously and remains critical in setting monetary policy in zero lower bound.

We develop an empirically based simulation study to test two types of policies designed to control systemic risk: preventive policies targeting capital requirements and mitigation policies targeting default resolution. We find that capital buffers reduce both the number of defaults and the resulting losses. The loss reduction benefit increases as the magnitude of adverse shocks becomes higher. We find that a simple branch-breakup resolution strategy reduces the loss borne by the Federal Deposit Insurance Corporation (FDIC). The mitigation effect becomes higher as the fraction of assets resolved through auctions and auction competitiveness increase.

Timely identification and anticipation of adverse conditions in the financial system are critical for macroprudential policy. However, there is no consensus on how to evaluate the quality of systemic measures. This paper provides a framework to compare measures of systemic conditions. We illustrate the proposed tests with a case study of US measures from 1976 to 2013. We find that measures which include information from multiple markets improve identification of critical system states. However, tested measures show limited capacity to anticipate critical episodes.

This paper builds on existing microprudential and macroprudential early warning systems (EWSs) to develop a new, hybrid class of models for systemic risk that incorporates the structural characteristics of the financial system and a feedback amplification mechanism. The models explain financial stress using both public and proprietary supervisory data from systemically important institutions, regressing institutional imbalances using an optimal lag method. The Systemic Assessment of Financial Environment (SAFE) EWS monitors microprudential information from the largest bank holding companies to anticipate the buildup of macroeconomic stresses in the financial markets. To mitigate inherent uncertainty, SAFE develops a set of medium-term forecasting specifications that gives policymakers enough time to take ex-ante policy action and a set of short-term forecasting specifications for verification and adjustment of supervisory actions. This paper highlights the application of these models to stress testing and policy.